In structural health monitoring (SHM) using electro-mechanical impedance signatures, it is a critical issue for extremely large structures to extract the best damage diagnosis results, while minimizing unknown environmental effects, including temperature, humidity, and acoustic vibration. If the impedance signatures fluctuate because of these factors, these fluctuations should be eliminated because they might hide the characteristics of the host structural damages. This paper presents a long-term SHM technique under an unknown noisy environment for tidal current power plant structures. The obtained impedance signatures contained significant variations during the measurements, especially in the audio frequency range. To eliminate these variations, a continuous principal component analysis was applied, and the results were compared with the conventional approach using the RMSD (Root Mean Square Deviation) and CC (Cross-correlation Coefficient) damage indices. Finally, it was found that this approach could be effectively used for long-term SHM in noisy environments.